Variable-mesh method of solving differential equations

Multistep predictor-corrector method for numerical solution of ordinary differential equations retains high local accuracy and convergence properties. In addition, the method was developed in a form conducive to the generation of effective criteria for the selection of subsequent step sizes in step-by-step solution of differential equations

Variable mesh multistep methods for ordinary differential equations

Variable mesh multistep methods for ordinary differential equation

Anaesthesia skills and simulation training during the COVID-19 pandemic

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The Influence Of Market Orientation, Flexibility And Job Satisfaction On Corporate Entrepreneurship

The profound dynamic changes that the South African business environment is going through and the low level of business development in the country begs for entrepreneurial innovation. This paper is an investigation into the relationship of corporate entrepreneurship with the organizational variables of marketing, flexibility and job satisfaction. These relationships are investigated in a sample of 333 managers in three different industries in South Africa. The relationships between corporate entrepreneurship and biographic variables were examined by means of Spearman correlation. Pearson-product moment correlation explored the association between corporate entrepreneurship and the organizational variables. The empirical results show significant relationships with different market orientation, flexibility, and job satisfaction factors. We suggest that organizations should nurture their corporate entrepreneurial strategies by fostering its orientation towards marketing, flexibility and job satisfaction

Alkaloidal variation in Cissampelos capensis (Menispermaceae)

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Context-aware support for cardiac health monitoring using federated machine learning

Context-awareness provides a platform for healthcare professionals to assess the health status of patients in their care using multiple relevant parameters such as heart rate, electrocardiogram (ECG) signals and activity data. It involves the use of digital technologies to monitor the health condition of a patient in an intelligent environment. Feedback gathered from relevant professionals at earlier stages of the project indicates that physical activity recognition is an essential part of cardiac condition monitoring. However, the traditional machine learning method f developing a model for activity recognition suffers two significant challenges; model overfitting and privacy infringements. This research proposes an intelligent and privacy-oriented context-aware decision support system for cardiac health monitoring using the physiological and the activity data of the patient. The system makes use of a federated machine learning approach to develop a model for physical activity recognition. Experimental analysis shows that the federated approach has advantages over the centralized approach in terms of model generalization whilst maintaining the privacy of the user

Context-aware system for cardiac condition monitoring and management: a survey

Health monitoring assists physicians in the decision-making process, which in turn, improves quality of life. As technology advances, the usage and applications of context-aware systems continue to spread across different areas in patient monitoring and disease management. It provides a platform for healthcare professionals to assess the health status of patients in their care using multiple relevant parameters. In this survey, we consider context-aware systems proposed by researchers for health monitoring and management. More specifically, we investigate different technologies and techniques used for cardiac condition monitoring and management. This paper also propose "mCardiac", an enhanced context-aware decision support system for cardiac condition monitoring and management during rehabilitation

The prediction of job involvement for pharmacists and accountants.

The job involvement of the individual seems to be potentially fundamental to the satisfaction of certain salient psychological needs that could lead to positive organizational implications. This study investigates the predictiveness of job involvement of 375 professionals in the pharmacy (n = 200) and accountancy (n = 175) occupations by means of Multiple Regression Analysis through personality characteristics and job satisfaction. A number of significant but weak relationships are reported varying between 1.29% and 9.85% common variance. Job involvement is predicted reasonably well for the total sample (19.35%) and the sub-samples of professionals (11.01% and 24.71% respectively)

Context-aware approach for cardiac rehabilitation monitoring

As technology advances, the usage and applications of context-aware systems continue to spread across different areas in patient monitoring and disease management. It provides a platform for healthcare professionals to assess the health status of patients in their care using multiple relevant parameters. Existing technologies for cardiac patient monitoring are generally based on the physiological information, mostly the heart rate or Electrocardiogram(ECG) Signals. Other important factors such as physical activities and time of the day are usually ignored. We propose a context-aware solution for cardiac rehabilitation monitoring using multiple vital signs from the physiological and activity data of the patient. This research considers the activity of the patient alongside the time of the activity to facilitate physicians decision-making process. We provide a personalised physical activity recognition processing by generating a personalised model for each user. A prototype is presented to illustrate our proposed approach

Simulation as an educational strategy to deliver interprofessional education

Background. Various educational methods are available to deliver interprofessional education (IPE) to prepare healthcare students for collaborative practice. One such method is simulation-based health education.Objectives. To identify current IPE methods used in undergraduate programmes in the Faculty of Health Sciences at the University of the Free State, Bloemfontein, South Africa, and to determine the opinions of module leaders on using simulation as a particular IPE teaching strategy.Methods. A quantitative, cross-sectional descriptive study design was employed. Structured interviews were conducted with 47 module leaders of the undergraduate programmes in the Faculty of Health Sciences. These programmes cover 66 modules in the Schools for Allied Health Professions (nutrition and dietetics, occupational therapy, physiotherapy and optometry), nursing and medicine.Results. At the time of the study, IPE activities were used in 29 (43.9%) of the modules, of which 17 (58.6%) were coincidental.  Respondents’ opinions on the potential use of simulation to address formalised IPE activities included the challenge of ‘scheduling’ (73.9%) and ‘logistical and high cost issues’ (19.6%). The most prominent advantage that was foreseen (41.3%) was better clarification of roles among the different professions.Conclusions. The module leaders had a positive attitude towards simulation and its potential use for IPE, with their major concern being logistical challenges. To improve role clarification, a scenario should be developed to engage students from all the relevant professions. The proposed type of simulation was to use standardised patients in a role-play scenario. The outcomes of these activities should be aligned with the principles of IPE